Yehao Li

Papers

1

Total Citations

4

H-Index

1

About

Yehao Li is a researcher specializing in embodied AI, robot manipulation, and learning from demonstrations. His work focuses on bridging the gap between simulation and real-world robotic control, particularly through the SAPIEN ManiSkill Challenge. In his highly cited paper, "Silver-Bullet-3D at ManiSkill 2021," Li presents a comparative analysis of systems designed for the No Interaction Track, where policies are learned solely from pre-collected demonstration trajectories. He investigates both imitation learning and heuristic rule-based methods, offering critical insights into how robots can acquire complex object manipulation skills without direct environment interaction. This contribution has been instrumental in advancing data-efficient learning for robotic tasks, earning recognition within the challenge community. Li’s research continues to push the boundaries of dexterous manipulation, making him a rising figure in the field of embodied AI.

Research Focus

Key Achievements

1
H-Index
1
Papers
4
Total Citations
4
Avg Citations/Paper
🏆 Most Cited Paper
Silver-Bullet-3D at ManiSkill 2021: Learning-from-Demonstrations and Heuristic Rule-based Methods for Object Manipulation
4 citations · 2022
📈 Most Prolific Year: 2022 (1 Papers)
🤝 Key Collaborators: 7

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago